CN109509161B - Image enhancement device and image enhancement method - Google Patents
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Abstract
The invention discloses an image enhancement device, comprising: the device comprises computer hardware, a color conversion module, an edge enhancement module and a saturation adjustment module. The computer hardware may be input with an image that includes red, green, and blue data. The color conversion module is used for converting the red, green and blue data into hue saturation brightness data, and after the image is enhanced, the color conversion module can be used for converting the hue saturation brightness data of the enhanced image into red, green and blue data. The edge enhancement module is used for detecting the plurality of pixels in the input image, finding a plurality of edge pixels from the plurality of pixels, and performing brightness performance enhancement on the plurality of edge pixels. The saturation adjusting module is used for adjusting the saturation of the edge pixels of the image. The edge enhancement module and the saturation adjustment module enhance the edge of the image and avoid the reduction of the edge pixel saturation of the image.
Description
Technical Field
The invention relates to an image enhancement device and an image enhancement method, which can simultaneously enhance the edge and the color of an image, improve the image enhancement efficiency and avoid the problem that the color of the image edge is dim when only the image edge is enhanced in the prior art.
Background
In the process of collecting, transmitting and converting an image in a computer or a related electronic device, the image quality may be reduced due to the influence of various factors, so that the image may have the phenomena of edge blurring, color fading and the like. Therefore, image enhancement is usually required in advance before an image is displayed on a liquid crystal display panel.
Image enhancement generally includes both types of image edge enhancement and image color enhancement. The image edge enhancement is to process the brightness component of the image edge pixel, so that the image edge is sharper in vision and clearer. Image color enhancement is processed on the saturation values of the image pixels to make the image color more vivid . In the prior art, the enhancement processes of the image edge enhancement and the image color enhancement are independent of each other. Edge enhancement of an image often causes the brightness of pixels at the edges of the image to change, while the saturation values and hue values of the pixels do not change. For the interpolated and enlarged image, when the image edge is enhanced, the color of the color pixel at the edge is darkened, for example, from bright red to dark red, resulting in the color at the edge being darkened and the saturation being deteriorated.
Therefore, it is necessary to provide an image enhancement apparatus and an image enhancement method to solve the problems of the prior art.
Disclosure of Invention
In view of the technical problems of the prior art, the present invention provides an image enhancement apparatus and an image enhancement method to solve the technical problems of the prior art.
The main object of the present invention is to provide an image enhancement apparatus and an image enhancement method, which can enhance the edge and color of an image simultaneously, improve the image enhancement efficiency, and avoid the problem of the prior art that the color of the image edge is dark when only the edge of the image is enhanced.
To achieve the above object, an image enhancement device of the present invention comprises:
computer hardware for inputting an image into the computer hardware, wherein the image comprises red, green, and blue data;
the color conversion module is arranged on the computer hardware and used for converting the red, green and blue data into hue saturation brightness data and converting the hue saturation brightness data of the enhanced image into red, green and blue data after the image is processed into the enhanced image;
an edge enhancement module, disposed in the computer hardware, for detecting a plurality of pixels in the input image, to find a plurality of edge pixels from the plurality of pixels, and to enhance the plurality of edge pixels; and
the saturation adjusting module is arranged on the computer hardware and used for adjusting the saturation of the edge pixels of the image;
after the color conversion module converts the red, green and blue data of the image into hue saturation brightness data, the edge enhancement module enhances the edge pixels in the image, the saturation adjustment module adjusts the saturation of the edge pixels of the image, the saturation of the edge pixels and the saturation difference of adjacent pixels adjacent to the edge pixels are increased to form an enhanced image, and finally the color conversion module converts the hue saturation brightness data of the enhanced image into the red, green and blue data.
In an embodiment of the invention, the rgb data includes a red value, a green value and a blue value of each pixel, and the hue saturation and brightness data includes a hue value, a saturation value and a brightness value.
In an embodiment of the present invention, the edge enhancement module is configured to perform an edge pixel detection step and an edge pixel performance enhancement step; the edge pixel detection step comprises performing brightness identification on the plurality of pixels in the image according to the brightness value in the hue saturation brightness data so as to find a plurality of edge pixels from the plurality of pixels; the edge pixel performance enhancing step includes adjusting the brightness value of the edge pixel so as to increase the brightness difference value between the edge pixel and the adjacent pixel.
In an embodiment of the present invention, the saturation adjusting module is configured to perform a saturation mean calculating step, a saturation difference calculating step, and a saturation adjusting step; the saturation mean calculating step includes taking each edge pixel of the image as a central pixel and calculating a saturation mean of adjacent pixels adjacent to the central pixel; the saturation difference calculating step includes calculating a saturation difference between the saturation of the central pixel and the saturation mean; the saturation adjusting step includes determining whether a saturation difference is greater than 0, if so, increasing the saturation of the central pixel, and if not, decreasing the saturation of the central pixel P1 to obtain the enhanced image.
In an embodiment of the present invention, the saturation average calculating step is based on the following equation: (S (j-1, i-1) + S (j-1, i) + S (j-1, i +1) + S (j, i-1) + S (j, i +1) + S (j +1, i-1) + S (j +1, i + 1))/8); wherein S _ av is a saturation mean value, and S (j-1, i-1), S (j-1, i +1), S (j, i-1), S (j, i +1), S (j +1, i-1), S (j +1, i +1)) is a saturation value of the adjacent pixel.
In an embodiment of the invention, the saturation difference calculating step is based on the following equation: f _ S ═ S (j, i) -S _ av; wherein S (j, i) is the saturation value of the central pixel, and f _ S is the saturation difference.
In an embodiment of the invention, the computer hardware includes a central processing unit, a memory, a storage, an input interface and an output interface electrically connected to each other, the input interface is used for inputting the image into the computer hardware, and the output interface is used for outputting the enhanced image.
Another object of the present invention is to provide an image enhancement method, comprising:
a computer providing step including providing computer hardware;
an image input step, comprising inputting an image to the computer hardware;
a first color data conversion step of converting, by the computer hardware, the input red, green, and blue data of the image into hue saturation brightness data;
an edge pixel detection step, including performing brightness identification on a plurality of pixels in the image according to the brightness values in the hue saturation brightness data through the computer hardware, so as to find a plurality of edge pixels from the plurality of pixels;
an edge pixel performance enhancing step, which includes adjusting, by the computer hardware, a brightness value of the edge pixel to increase a brightness difference between the edge pixel and an adjacent pixel;
a saturation adjustment step comprising adjusting, by the computer hardware, a saturation of an edge pixel of the image, increasing the edge pixel saturation and a saturation difference of an adjacent pixel adjacent to the edge pixel to form an enhanced image; and
a second color conversion step comprising converting, by said computer hardware, hue saturation luminance data contained in said enhanced image to red green blue data.
In an embodiment of the invention, the rgb data includes a red value, a green value and a blue value of each pixel; the hue saturation luminance data includes a hue value, a saturation value, and a luminance value.
In an embodiment of the present invention, the saturation adjusting step includes:
a saturation mean calculation step of taking each edge pixel of the image as a central pixel and calculating a saturation mean of adjacent pixels adjacent to the central pixel;
a saturation difference calculation step including calculating a saturation difference between the saturation of the central pixel and the saturation mean; and
and a saturation adjusting step, including judging whether the saturation difference is greater than 0, if so, increasing the saturation of the central pixel, and if not, decreasing the saturation of the central pixel P1, thereby obtaining the enhanced image. Compared with the prior art, the image enhancement device and the image enhancement method have the following advantages:
1. after the sharpness of the image edge is enhanced and the saturation is adjusted through the method, the sharpness of the image can be improved, the saturation of the image edge pixels can be kept, and the image is prevented from being dark.
2. The method has simple formula, avoids overlarge calculation burden of computer hardware, and can improve the image quality and avoid increasing the burden of the computer hardware.
In order to make the aforementioned and other objects of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below:
drawings
FIG. 1 is a block diagram illustrating the hardware and software architecture of an image enhancement device according to the present invention.
FIG. 2 is a schematic diagram of a function execution architecture of the image enhancement apparatus according to the present invention.
FIG. 3 is a schematic processing flow diagram of the image enhancement apparatus according to the present invention.
FIG. 4 is a diagram of a plurality of pixels in an image.
FIG. 5 is a flowchart illustrating steps of an image enhancement method according to the present invention.
Detailed Description
Referring to fig. 1 and fig. 2, fig. 1 is a block diagram illustrating a hardware and software architecture of an image enhancement device according to the present invention, and fig. 2 is a functional execution architecture diagram of the image enhancement device according to the present invention. The image enhancement device of the present invention includes: computer hardware 10, color conversion module 20, edge enhancement module 30, saturation adjustment module 40.
The computer hardware 10 includes a central processing unit 11, a memory 12, a storage 13, an input interface 14 and an output interface 15 electrically connected to each other.
The Memory 12 may be a Random access Dynamic Memory (DRAM) 12.
The storage 13 may be a Hard Disk Drive (HDD) or a Solid State Drive (SSD).
The input interface 14 may be an electrical connector, such as a Universal Serial Bus (USB) electrical connector, for inputting a graphic 16 into the computer hardware 10. The image 16 input to the computer hardware 10 comprises a plurality of pixels and comprises Red, Green, Blue (RGB) data, the RGB data 160 comprising a Red value, a Blue value and a Green value for each pixel. The RGB data 160 may be converted into Hue Saturation Luminance (HSL) data, which includes a Hue value H, a Saturation value S, and a luminance value L. In addition, the image 16 can be stored in the memory 13 after being input to the computer hardware 10, and can be loaded into the memory 12 for processing by the central processing unit 11.
The output Interface 15 may be an electrical connector, such as a High Definition Multimedia Interface (HDMI) connector, for outputting images to an external electronic device, such as a liquid crystal display panel.
Fig. 3 is a schematic processing flow chart of the image enhancement device according to the present invention. In detail, the computer hardware 10 itself may perform the image input step S02, including inputting an image 160 to the computer hardware 10.
The color conversion module 20, disposed in the computer hardware 10, may be stored in the memory 13 as software, and is used for converting the RGB data 160 into HSL data and for converting the HSL data into the RGB data 160. The color conversion module 20 may convert the input RGB data 160 of the image 16 into HSL data. In detail, the color conversion module 20 may perform a first color data conversion step S03, including converting the input RGB data 160 of the image 16 into HSL data.
The edge enhancement module 30, disposed in the computer hardware 10, may be stored in the storage 13 as software, and is configured to detect the plurality of pixels in the input image 16, to find a plurality of edge pixels from the plurality of pixels, and to perform brightness performance enhancement on the plurality of edge pixels. The edge pixels mentioned herein may be pixels on the inner or outer contour of a person, an object, or a scene in the image in a general case, for example, the pixels on the contour at the boundary between a face and a background in the image are edge pixels. In addition, in detail, the edge enhancement module 30 may perform the following steps: an edge pixel detection step S04 and an edge pixel performance enhancement step S05.
The edge pixel detecting step S04 includes performing brightness recognition on the pixels in the image 16 according to the brightness value L in the HSL data to find a plurality of edge pixels from the pixels.
The edge pixel performance enhancing step S05 includes adjusting the brightness value L of the edge pixel so as to increase the brightness difference value between the edge pixel and the adjacent pixel. Generally, the adjustment of the luminance value L includes decreasing the luminance of the edge pixel to increase the luminance difference between the edge pixel and the adjacent pixel, thereby providing the sharpness of the contour of the person, object, and scene included in the image 16. Through the edge pixel performance enhancing step S05, the brightness difference between the edge pixel and the adjacent pixel can be enlarged, thereby increasing the sharpness of people, objects, and scenes in the image 16.
The saturation adjustment module 40, disposed in the computer hardware 10, may be stored in the memory 13 as software, and is configured to adjust the saturation of the edge pixel of the image 16, and increase the saturation of the edge pixel and the saturation difference of the adjacent pixels adjacent to the edge pixel to form an enhanced image. In detail, the saturation adjustment module 40 may perform a saturation adjustment step S06, including adjusting the saturation of edge pixels of the image 16. In detail, the saturation adjusting step S06 includes: a saturation mean calculation step S06A, a saturation difference calculation step S06B, and a saturation adjustment step S06C.
Please refer to fig. 4, which is a schematic diagram of a plurality of pixels in the image 16. The saturation mean calculation step S06A includes regarding each edge pixel of the image 16 as a central pixel P1 (whose coordinates are (j, i)), and calculating a saturation mean S _ av of an adjacent pixel P2 adjacent to the central pixel P1. For example, in the 9 pixels in the 3 × 3 matrix shown in fig. 4, the pixel at the center is the edge pixel, which is also the center pixel P1, and the remaining 8 pixels are the neighboring pixels P2. The detailed calculation is as follows equation 1:
equation 1: s _ av ═ S (j-1, i-1) + S (j-1, i +1) + S (j, i-1) + S (j, i +1) + S (j +1, i-1) + S (j +1, i + 1))/8.
The saturation difference calculation step S06B includes calculating a saturation difference f _ S between the saturation S (j, i) of the center pixel and the saturation mean S _ av. The detailed calculation is as follows in equation 2:
equation 2: f _ S ═ S (j, i) -S _ av.
As can be seen from the saturation difference calculation step S06B, the saturation S (j, i) of the center pixel P1 increases or decreases by an amount proportional to f _ S.
The saturation adjustment step S06C includes determining whether the saturation difference f _ S is greater than 0, if f _ S >0, increasing the saturation S (j, i) of the central pixel P1, and if f _ S <0, decreasing the saturation S (j, i) of the central pixel P1, thereby obtaining an enhanced image 16a, as shown in fig. 1.
The computer hardware 10 then converts the HSL data contained in the enhanced image 16a to RGB data 160. In detail, the computer hardware may perform a second color conversion step S07, comprising converting the HSL data contained in the enhanced image 16a into RGB data 160.
Finally, the computer hardware 10 outputs the enhanced image 16a to the electronic device 50 through the output interface 15, for example, to a liquid crystal display panel, so that the image presented by the electronic device 50 is the enhanced image 16a with proper sharpness and saturation. In detail, the computer hardware 10 may perform an image output step S08, including outputting the enhanced image 16a to the electronic device 50 through the output interface 15 of the computer hardware 10.
Referring to fig. 4 and 5, fig. 5 is a flowchart illustrating steps of an image enhancement method according to the present invention. The image enhancement method comprises the following steps: the computer provides step S01, image input step S02, first color data conversion step S03, edge pixel detection step S04, edge pixel performance enhancement step S05, saturation adjustment step S06, second color conversion step S07, and image output step S08.
The computer providing step S01 includes providing a piece of computer hardware 10 as described in fig. 1.
The image input step S02 includes inputting an image 160 to the computer hardware 10.
The first color data conversion step S03 includes converting the input RGB data 160 of the image 16 into HSL data by the computer hardware 10.
The edge pixel detecting step S04 includes performing, by the computer hardware 10, luminance recognition on the plurality of pixels in the image 16 according to the luminance value L in the HSL data to find a plurality of edge pixels from the plurality of pixels.
The edge pixel performance enhancing step S05 includes adjusting, by the computer hardware 10, the luminance value L of the edge pixel so that the luminance difference between the edge pixel and the adjacent pixel is increased.
The saturation adjusting step S06 includes adjusting, by the computer hardware 10, the saturation of edge pixels of the image 16. In detail, the saturation adjusting step S06 includes the saturation mean calculating step S06A, the saturation difference calculating step S06B, and the saturation adjusting step S06C.
The second color conversion step S07 includes converting, by the computer hardware 10, the HSL data contained in the enhanced image 16a into RGB data 160.
The image outputting step S08 includes outputting, by the computer hardware 10, the enhanced image 16a to the electronic device 50 through the output interface 15 of the computer hardware 10.
Compared with the prior art, the image enhancement device and the image enhancement method have the following advantages:
1. after the sharpness of the image edge is enhanced and the saturation is adjusted through the method, the sharpness of the image can be improved, the saturation of the image edge pixels can be kept, and the image is prevented from being dark.
2. The method has simple formula, avoids overlarge calculation burden of computer hardware, and can improve the image quality and avoid increasing the burden of the computer hardware.
Claims (7)
1. An image enhancement apparatus characterized by: the image enhancement device includes:
computer hardware for providing an image for input into said computer hardware, wherein said image comprises red, green and blue data;
the color conversion module is arranged on the computer hardware and used for converting the red, green and blue data into hue saturation brightness data and converting the hue saturation brightness data of the enhanced image into red, green and blue data after the image is processed into the enhanced image;
an edge enhancement module, disposed in the computer hardware, for detecting a plurality of pixels in the input image, to find a plurality of edge pixels from the plurality of pixels, and performing brightness performance enhancement on the plurality of edge pixels; and
the saturation adjusting module is arranged on the computer hardware and used for adjusting the saturation of the edge pixels of the image;
after the color conversion module converts the red, green and blue data of the image into hue saturation brightness data, the edge enhancement module enhances brightness performance of the edge pixels in the image, the saturation adjustment module adjusts the saturation of the edge pixels of the image, the saturation of the edge pixels and the saturation difference of adjacent pixels adjacent to the edge pixels are increased to form an enhanced image, and finally the color conversion module converts the hue saturation brightness data of the enhanced image into red, green and blue data;
the red, green and blue data comprise a red value, a green value and a blue value of each pixel, and the hue saturation and brightness data comprise a hue value, a saturation value and a brightness value;
the saturation adjusting module is configured to perform a saturation mean value calculating step, a saturation difference value calculating step, and a saturation adjusting step, where the saturation mean value calculating step includes using each edge pixel of the image as a central pixel and calculating a saturation mean value of adjacent pixels adjacent to the central pixel, the saturation difference value calculating step includes calculating a saturation difference value between the saturation of the central pixel and the saturation mean value, and the saturation adjusting step includes determining whether the saturation difference value is greater than 0, increasing the saturation of the central pixel if the saturation difference value is greater than 0, and decreasing the saturation of the central pixel if the saturation difference value is less than 0, thereby obtaining the enhanced image.
2. The image enhancement apparatus according to claim 1, characterized in that: the edge enhancement module is used for executing an edge pixel detection step and an edge pixel performance enhancement step; the edge pixel detection step includes performing brightness recognition on the plurality of pixels in the image according to the brightness values in the hue saturation brightness data to find a plurality of edge pixels from the plurality of pixels, and the edge pixel performance enhancement step includes adjusting the brightness values of the edge pixels to increase the brightness difference between the edge pixels and adjacent pixels.
3. The image enhancement apparatus according to claim 2, characterized in that: the saturation mean calculation step is based on the following equation: s _ av ═ S (j-1, i-1) + S (j-1, i +1) + S (j, i-1) + S (j, i +1) + S (j +1, i-1) + S (j +1, i) + S (j +1, i +1))/8, where S _ av is the saturation mean, and S (j-1, i-1), S (j-1, i +1), S (j, i-1), S (j, i +1), S (j +1, i-1), S (j +1, i +1)) are the saturation values of the neighboring pixels.
4. The image enhancement apparatus according to claim 2, characterized in that: the saturation difference calculation step is based on the following equation: s (j, i) -S _ av, where S (j, i) is the saturation value of the center pixel and f _ S is the saturation difference.
5. The image enhancement apparatus according to claim 1, characterized in that: the computer hardware comprises a central processing unit, a memory, a storage, an input interface and an output interface which are mutually and electrically connected, wherein the input interface is used for inputting the image into the computer hardware, and the output interface is used for outputting the enhanced image.
6. An image enhancement method, comprising:
a computer providing step including providing computer hardware;
an image input step, comprising inputting an image to the computer hardware;
a first color data conversion step of converting, by the computer hardware, the input red, green, and blue data of the image into hue saturation brightness data;
an edge pixel detection step, including performing brightness identification on a plurality of pixels in the image according to the brightness values in the hue saturation brightness data through the computer hardware, so as to find a plurality of edge pixels from the plurality of pixels;
an edge pixel performance enhancing step, which includes adjusting, by the computer hardware, a brightness value of the edge pixel to increase a brightness difference between the edge pixel and an adjacent pixel;
a saturation adjustment step comprising adjusting, by the computer hardware, a saturation of an edge pixel of the image, increasing the edge pixel saturation and a saturation difference of an adjacent pixel adjacent to the edge pixel to form an enhanced image; and
a second color conversion step comprising converting hue saturation luminance data contained in said enhanced image into red green blue data by said computer hardware;
the saturation adjusting step includes:
a saturation mean calculation step of taking each edge pixel of the image as a central pixel and calculating a saturation mean of adjacent pixels adjacent to the central pixel;
a saturation difference calculation step including calculating a saturation difference between the saturation of the central pixel and the saturation mean; and
and a saturation adjusting step, including judging whether the saturation difference is greater than 0, if so, increasing the saturation of the central pixel, and if not, reducing the saturation of the central pixel, thereby obtaining the enhanced image.
7. The image enhancement method of claim 6, wherein: the RGB data includes a red value, a green value and a blue value of each pixel, and the hue saturation and brightness data includes a hue value, a saturation value and a brightness value.
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